A simplified glowworm swarm optimization algorithm

Aimed at the poor optimizing ability and the low accuracy of the glowworm swarm optimization algorithm (GSO), a simplified glowworm swarm optimization algorithm (SGSO) was put forward in this paper, which omitted the phases of seeking dynamic decision domain and movement probability calculation, and meanwhile simplified the location updating process. Moreover, elitism was introduced to improve the capacity of searching optimal solution. It was applied to the unimodal and multimodal benchmark function optimization problems. The improved SGSO algorithm is compared with the basic GSO and other swarm intelligent optimization algorithms to demonstrate the performance. Experimental results showed that SGSO improves not only the precision but also the efficiency in function optimization.